People with ALS eventually and inevitably experience serious speech impairment due to progressive deterioration of brain cells that control movements of the tongue, lips and jaw. Despite the devastating consequences of this speech impairment on quality of life and survival, few options are available to assist impaired oral communication, and many existing speech-generating technologies are slow to operate and cost prohibitive. This project seeks to improve quality of life for persons with impaired speech due to ALS by testing the effectiveness of a low-cost, speech-generating device (a virtual vocal tract) that could significantly prolong the ability of these patients to communicate orally. If successful, these techniques could be extended for use by patients' with a broad range of speech motor impairments. The virtual vocal track uses machine learning algorithms to predict what a person is attempting to say, in real-time, based solely on lip movements. Users of the device are able to trigger the playback of a number of predetermined phrases by simply attempting to articulate what they want to say. Our previous work has shown the feasibility of this approach using cost-prohibitive laboratory systems such as electromagnetic articulography. Recent advances in 3D depth mapping camera technology allow these techniques to be tested for the first time using technologies, which are low-cost, portable and already being integrated into consumer devices such as laptops and cellphones. To this end, the system under development will be tested in 60 patients with ALS, representing a range of speech impairment from normal to severe speech intelligibility (15 normal, 15 mild, 15 moderate, 15 severe). During testing, participants will be cued to articulate the phrases in a random order as fast as is comfortable for them. The entire session will be recorded and the following variables will be measured offline: recognition accuracy, recognition latency, task time, % completion, and communication rate (words per minute). Users will rate the usability and acceptability of the virtual vocal tract immediately following device testing, using the System Usability Scale. Results of this testing will be used to address the following specific aims: (1) Determine the accuracy and latency of real-time phrase synthesis based on dysarthric speech using the virtual vocal tract, (2) Determine the usability and acceptability of real-time phrases produced using the virtual vocal tract, and (3) Identify the articulatory and speech factors that degrade recognition accuracy.